| Title: |
Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization. |
| Authors: |
Willems, SM; Ng, NHJ; Fernandez, J; Fine, RS; Wheeler, E; Wessel, J; Kitajima, H; Marenne, G; Sim, X; Yaghootkar, H; Wang, S; Chen, S; Chen, Y; Chen, Y-DI; Grarup, N; Li-Gao, R; Varga, TV; Asimit, JL; Feng, S; Strawbridge, RJ; Kleinbrink, EL; Ahluwalia, TS; An, P; Appel, EV; Arking, DE; Auvinen, J; Bielak, LF; Bihlmeyer, NA; Bork-Jensen, J; Brody, JA; Campbell, A; Chu, AY; Davies, G; Demirkan, A; Floyd, JS; Giulianini, F; Guo, X; Gustafsson, S; Jackson, AU; Jakobsdottir, J; Järvelin, M-R; Jensen, RA; Kanoni, S; Keinanen-Kiukaanniemi, S; Li, M; Lu, Y; Luan, J; Manning, AK; Marten, J; Meidtner, K; Mook-Kanamori, DO; Muka, T; Pistis, G; Prins, B; Rice, KM; Sanna, S; Smith, AV; Smith, JA; Southam, L; Stringham, HM; Tragante, V; van der Laan, SW; Warren, HR; Yao, J; Yiorkas, AM; Zhang, W; Zhao, W; Graff, M; Highland, HM; Justice, AE; Marouli, E; Medina-Gomez, C; Afaq, S; Alhejily, WA; Amin, N; Asselbergs, FW; Bonnycastle, LL; Bots, ML; Brandslund, I; Chen, J; Danesh, J; de Mutsert, R; Dehghan, A; Ebeling, T; Elliott, P; EPIC-Interact Consortium; Farmaki, A-E; Faul, JD; Franks, PW; Franks, S; Fritsche, A; Gjesing, AP; Goodarzi, MO; Gudnason, V; Hallmans, G; Harris, TB; Herzig, K-H; Hivert, M-F; Jørgensen, T; Jørgensen, ME; Jousilahti, P; Kajantie, E; Karaleftheri, M; Kardia, SLR; Kinnunen, L; Koistinen, HA; Komulainen, P; Kovacs, P; Kuusisto, J; Laakso, M; Lange, LA; Launer, LJ; Leong, A; Lindström, J; Manning Fox, JE; Männistö, S; Maruthur, NM; Moilanen, L; Mulas, A; Nalls, MA; Neville, M; Pankow, JS; Pattie, A; Petersen, ERB; Puolijoki, H; Rasheed, A; Redmond, P; Renström, F; Roden, M; Saleheen, D; Saltevo, J; Savonen, K; Sebert, S; Skaaby, T; Small, KS; Stančáková, A; Stokholm, J; Strauch, K; Tai, E-S; Taylor, KD; Thuesen, BH; Tönjes, A; Tsafantakis, E; Tuomi, T; Tuomilehto, J; Understanding Society Scientific Group; Uusitupa, M; Vääräsmäki, M; Vaartjes, I; Zoledziewska, M; Abecasis, G; Balkau, B; Bisgaard, H; Blakemore, AI; Blüher, M; Boeing, H; Boerwinkle, E; Bønnelykke, K; Bottinger, EP; Caulfield, MJ; Chambers, JC; Chasman, DI; Cheng, C-Y; Collins, FS; Coresh, J; Cucca, F; de Borst, GJ; Deary, IJ; Dedoussis, G; Deloukas, P; den Ruijter, HM; Dupuis, J; Evans, MK; Ferrannini, E; Franco, OH; Grallert, H; Hansen, T; Hattersley, AT; Hayward, C; Hirschhorn, JN; Ikram, A; Ingelsson, E; Karpe, F; Kaw, K-T; Kiess, W; Kooner, JS; Körner, A; Lakka, T; Langenberg, C; Lind, L; Lindgren, CM; Linneberg, A; Lipovich, L; Liu, C-T; Liu, J; Liu, Y; Loos, RJF; MacDonald, PE; Mohlke, KL; Morris, AD; Munroe, PB; Murray, A; Padmanabhan, S; Palmer, CNA; Pasterkamp, G; Pedersen, O; Peyser, PA; Polasek, O; Porteous, D; Province, MA; Psaty, BM; Rauramaa, R; Ridker, PM; Rolandsson, O; Rorsman, P; Rosendaal, FR; Rudan, I; Salomaa, V; Schulze, MB; Sladek, R; Smith, BH; Spector, TD; Starr, JM; Stumvoll, M; van Duijn, CM; Walker, M; Wareham, NJ; Weir, DR; Wilson, JG; Wong, TY; Zeggini, E; Zonderman, AB; Rotter, JI; Morris, AP; Boehnke, M; Florez, JC; McCarthy, MI; Meigs, JB; Mahajan, A; Scott, RA; Gloyn, AL; Barroso, I |
| Publisher Information: |
Wellcome |
| Publication Year: |
2023 |
| Collection: |
Queen Mary University of London: Queen Mary Research Online (QMRO) |
| Subject Terms: |
EPIC-Interact Consortium; Understanding Society Scientific Group |
| Description: |
Background Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways. Methods To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses. Results Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology. Conclusions Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries. |
| Document Type: |
article in journal/newspaper |
| File Description: |
483 - ?; Electronic-eCollection |
| Language: |
English |
| Relation: |
Wellcome open research; https://qmro.qmul.ac.uk/xmlui/handle/123456789/103546 |
| DOI: |
10.12688/wellcomeopenres.18754.1 |
| Availability: |
https://qmro.qmul.ac.uk/xmlui/handle/123456789/103546; https://doi.org/10.12688/wellcomeopenres.18754.1 |
| Rights: |
This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ; © 2023 Willems SM et al. |
| Accession Number: |
edsbas.E02A6440 |
| Database: |
BASE |